Curriculum Vitae Detail

Faculty & Staff

Mohammad Biswas

Associate Professor


Current Positions

  • Assistant Professor
  • Associate Professor

Contact Information

Office Number: A214

Office Building: HEC

Email Address: mbiswas@uttyler.edu

Work Phone: (903)566-6115

Degrees

2013

Ph.D., Chemical Engineering, University of Florida, Gainesville, Florida

Dissertation: Modeling and controls of a fuel cell system in portable devices

2008

B.S., Chemical Engineering, Auburn University, Auburn, Alabama

Dissertation: Investigation of non-chlorinated precursor compounds for molecular vapor deposition of silica

Work Experience

2020 - Ongoing

Associate Professor, University of Texas at Tyler, Houston, Texas, United States.

2017 - 2021

Faculty Research Associate (Engineer), NASA, houston, Texas.

2014 - 2020

Assistant Professor, University of Texas at Tyler, Houston, Texas.

2015 - 2017

Faculty Research Associate (Software Developer), NASA, houston, Texas.

Scholarly Contributions and Creative Productions

Journal Publication

Mohammad Biswas, Tabbi Wilberforce, Mohammad Biswas (2023). Prediction of Transient Hydrogen Flow of Proton Exchange Membrane Electrolyzer Using Artificial Neural Network. Hydrogen, 4(3), 542-555.

Christian Pirruccio, Kiril Nikolov, Mohammad Biswas (2023). <span>Compliant EVA Sample Size Location and Calibration Marker </span>. International Journal of Student Project Reporting, 1(3), 261-282.

Tabbi Wilberforce, Mohammad Biswas (2023). <span>Dynamic Thermal Model Development of Direct Methanol Fuel Cell Using Artificial Neural Network</span>. International Journal of Thermofluids, 17, 100294.

Jorian Khan, Mohammad Biswas, Tabbi Wilberforce (2023). DEVELOPMENT OF AN EDUCATIONAL FUEL CELL SYSTEM FOR MECHANICAL ENGINEERING COURSE. International Journal on Engineering, Science and Technology

Tabbi Wilberforce, Mohammad Biswas, Abdelnasir Omran (2022). Power and Voltage Modelling of a Proton-Exchange Membrane Fuel Cell Using Artificial Neural Networks . Energies, 15(5587)

Wilberforce, T.; Biswas, M.; Omran, A. Power and Voltage Modelling of a Proton-Exchange Membrane Fuel Cell Using Artificial Neural Networks. Energies 2022, 15, 5587. https://doi.org/10.3390/en15155587

Patent

William Lear, Jr., Oscar Crisalle, Shyam Mudiraj, Mohammad Biswas (2019). Operational control of fuel cells

Direct methanol fuel cells continuously require water to react with the methanol fuel at the anode side of the cell; it is generally obtained from the water produced on the cathode side. Until now, water management in DMFCs has required a bulky system of fans, exit condensers and other components for recapturing evaporated water from the exiting cathode air stream. Researchers have created a fuel cell with an innovative structure that forces water to flow directly from the cathode into the anode stream. Microscale passages within the DMFC reroute water and effectively prevent water losses to the air using much less space. Optimal water balance during fuel cell operation is achieved with innovative algorithms that adjust fuel and oxidizer injection rates in response to power load demands. As a result, no excess water is generated. These researchers also developed an inexpensive method for measuring fuel concentration. It eliminates the need for expensive in-place fuel sensors and can collect information about temperature, fuel-level, stack currents, fan speed and fuel-injection pump output rates through the use of a computer algorithm.

Poster Presentation

Gokay Aygun, Anh Nguyen, Daniel Vasek, Mohammad Biswas (2021). Design of a User Friendly Remotely Accessible Cross Flow Heat Exchanger . Virtual

Suvam Pokhrel, Sarju Patel, Ishfar Ahmed, Mohammad Biswas (2021). A Comparative Analysis of Fuel Cell and Internal Combustion Engine in Automobile Application . Virtual

Mohammad Biswas, Kamwana Mwara (2020). Model Development of Solid Oxide Fuel Cell Thermal Performance Using Artificial Neural Network. Virtual. AIChE.

Session: Spring Meeting & GCPS Poster Session scheduled for Wednesday, August 19, 2020: 3:00 PM - 4:00 PM, vFairs Virtual Platform, Poster Sessions (60au) Model Development of Solid Oxide Fuel Cell Thermal Performance Using Artificial Neural Network NASA’s Johnson Space Center has recently begun efforts to eventually integrate air-independent Solid Oxide Fuel Cell systems, with landers that can be propelled by LOX-CH4, for long duration missions. Using landers that utilize such propellants, provides the opportunity to use such systems as a power option, especially since they will be able to process methane into a reactant through fuel reformation. To ensure fuel reformation in the systems, Steam Methane Reformation (SMR) will be employed. Various lead-up activities, such as hardware testing and computational modelling, have been initiated to assist with this developmental effort including the development of dynamic empirical models using artificial neural network. Such a modeling approach has shown to be accurate (R^2>0.9) to predict the thermal and electrical performance for SOFC systems. Hence, such models could be used for system optimization and control design.

Mohammad Biswas (2020). Analysis of Fuel Cell System through Project Based Learning for Application of Classical Thermal Fluid Concepts in Mechanical Engineering Laboratory Course. Virtual. AIChE.

Session: Spring Meeting & GCPS Poster Session scheduled for Wednesday, August 19, 2020: 3:00 PM - 4:00 PM, vFairs Virtual Platform, Poster Session (60an) Analysis of Fuel Cell System through Project Based Learning for Application of Classical Thermal Fluid Concepts in Mechanical Engineering Laboratory Course A hands-on project involving analysis of air noncircular channels in Fuel Cell to measure the pressure was introduced in a thermal fluid laboratory course. Although the students studied fluid mechanics as a theoretical course, this project gave them the opportunity to build an experimental setup from scratch to help showcase their hands-on skills and to apply their understanding of relevant concepts of fluid sciences. The results of the project included a successful test of a conceptual procedure, designed to measure and calculate pressure drop and flow rates across the anode and cathode sides of a fuel cell. The students enjoyed completing and learning from the project. They also provided very useful feedback on the project by incorporating a functional experimental system for the future laboratory project. This project based learning opportunity allowed students to build their confidence in what they are learning as well as provide a glimpse of what the real world may hold.

Presentation

Mohammad Biswas (2023). Hands on project based learning activity. Bush House, Strand Campus, London. King’s College London.

Presented virtually on Sept 5

Samuel Ogletree, Mohammad Biswas (2019). A Review of Solid Oxide Electrolyzer Cell (SOEC) Modeling of Dry Carbon Dioxide Electrolysis . Tyler, TX. The University of Texas at Tyler.

Jared Reynolds, Samuel Ogletree, Andrew Hughes, Kelvin Lim, Michael Mahaffey, Mohammad Biswas, Chung Goh (2019). Development and Analysis of a Control Architecture for a Laboratory-Scale, Double Pipe Heat Exchanger . Tyler, TX. The University of Texas at Tyler.

Proceedings Publication

Mo'ath Mossad, Mohammad Biswas, Muath Salim, Hassan El-Kishky, Nael Barakat (2023). Artificial Neural Network Based Model for Reverse Osmosis Water Desalination Membrane. International Congress on Sustainability Science & Engineering (ICOSSE) . Houston

Availability of fresh drinking water continues to be a major concern around the globe. One of the most effective methods to provide fresh drinking water is through the use of desalination plants. Over the past years, reverse osmosis (RO) membrane technology has developed significantly, gained popularity, and become the most widely used desalination technology for both seawater and brackish water, due to advancements in membrane technology and improvements in energy efficiency resulting in higher performance and reduced cost. On the other hand, the modeling of RO membranes is challenging due to the complexity of the analytic models and the lack of the membrane’s characteristics. This work provides a multi-input-output Artificial Neural Network (ANN) model to predict the membrane’s characteristics at different flow conditions. ANN is a biologically inspired computer program that is constructed to mimic the way in which the human brain handles information, and it has been used widely to model different systems especially nonlinear and/ or complex systems. This model can be used to reduce the modeling complexity of the membrane and to predict the freshwater flow rate and salinity at different conditions by using a set of experimental data for the membrane. The model uses the feedwater pressure, flowrate, and salinity to predict the freshwater flowrate and salinity. The model shows correction value (R)of 0.985 for the testing data and it is capable to predict the membrane’s characteristics at pressure values from 90 to 160 psi.

Mohammad Biswas, Mohammad Biswas, Muath Salim, Tabbi Wilberforce (2023). Remaining Useful Life Estimation of Proton Exchange Membrane Fuel Cells Using Artificial Neural Network. International Congress on Sustainability Science & Engineering (ICOSSE). Houston

Mohammod Rahman, Mohammad Biswas (2023). A Computational Fluid Dynamics Approach for the Modeling of CO2 Separation from Flue Gas in Membrane Modules. The International Conference and Exhibition for Science

Mohammad Biswas, Mohammod Rahman (2023). Computational Fluid Dynamics Modelling of a Solid Oxide Electrochemical System. The International Conference and Exhibition for Science

Mohammad Biswas, Ola Al-Shalash, Nael Barakat (2022). Remote Laboratory-Based Learning in A Thermal Fluid Course. ASEE Annual Conference and Exposition. Minneapolis

Mohammad Biswas, Jorian Khan (2022). DEVELOPMENT OF AN EDUCATIONAL FUEL CELL SYSTEM<br>FOR MECHANICAL ENGINEERING COURSE. International Conference on Engineering, Science and Technology (IConEST) . Austin

Mohammad Biswas, Oswaldo Garcia, Luis Reyes, Seyed Hoshivar, Ruaa Salman, Vladislav Kurmishev (2022). <span style="font-size:10pt;">Energy and Cost Analysis of Ground Source Heat Pump Systems for Residential Application in Texas</span>. International Conference on Studies in Engineering, Science, and Technology (ICSEST). Antalya, TURKEY

Mohammad Biswas, Jorian Khan (2022). <span><span>INTERNALLY DEVELOPED OPEN EDUCATIONAL</span><span> </span><span>TEXTBOOK FOR </span><span>THERMAL FLUID LABORATORY COURSE</span></span>. International Conference on Studies in Engineering, Science, and Technology (ICSEST). Antalya, TURKEY

Mohammad Biswas, Benjamin Stilwell, Edgar Reyes (2021). Simulated Laboratory-Based Learning In A Thermal Fluid Laboratory Course. ASEE Gulf Southwest Annual Conference. Waco

Edgar Reyes, Benjamin Stilwell, Jongin Sithideth, Christian Puckett, Christopher Nobinger, Cassandra Ellis, Andres Garcia, Mohammad Biswas (2021). Design of An Innovative Module for Mars Habitation. ASEE Gulf Southwest Annual Conference. Waco

Mohammad Biswas, Benjamin Stilwell, Edgar Reyes (2021). Thermal Model Development and Control Design Interface of a PEM Fuel Cell for Simulation Based Learning in a Mechanical Engineering Course. ASEE Southeastern Section Conference. Virtual

Mohammad Biswas, Aws Al-Shalash (2021). Improve Technical Communication Using Scaffolding Method in Mechanical Engineering Courses. 2021 Fall ASEE Middle Atlantic Section Conference. Virtual

Nael Barakat, Aws Al-Shalash, Mohammad Biswas, Shih-Feng Chou, Tahsin Khajah (2021). Engineering Experiential Learning During the COVID-19 Pandemic. Interactive Collaborative Learning

Nael Barakat, Aws Al-Shalash, Mohammad Biswas, Shih-Feng Chou, Tahsin Khajah (2021). Engineering Experiential Learning During the COVID-19 Pandemic. International Conference on Interactive Collaborative Learning (ICL). Tu and HTW Dresden, Germany

Mohammad Biswas, Aws Al-Shalash (2021). Improve Technical Communication using Scaffolding Method in Mechanical Engineering Course. ASEE - MAS

Kiril Nikolov, Xuan Nguyen, Victor Ortiz, Mohammad Biswas (2021). Simulated Crossflow Heat Exchanger System Using Simulink Modeling . 2021 Fall ASEE Middle Atlantic Section Conference. Virtual

Nael Barakat, Aws Al-Shalash, Mohammad Biswas, Shih-Feng Chou, Tahsin Khajah (2021). Engineering Experiential Learning During the COVID-19 Pandemic. International Conference on Interactive Collaborative Learning (ICL). Tu and HTW Dresden, Germany

Samuel Ogltree, Mohammad Biswas (2020). Thermal Fluid Analysis of a Solid Oxide Electrolyzer Cell for Oxygen Production from Carbon Dioxide. 2020 Spring Meeting & 16th Global Congress on Process Safety. Virtual

ABSTRACT ACCEPTED; Available via Online access to proceedings from Spring AIChE meetings (65b) Thermal Fluid Analysis of a Solid Oxide Electrolyzer Cell for Oxygen Production from Carbon Dioxide The development of novel life support systems is necessary for human exploration of Mars. A major resource that is required is breathable oxygen. A promising approach is the use of a Solid Oxide Electrolyzer Cell (SOEC) to reduce the carbon dioxide in the Martian atmosphere (96% by volume) to oxygen. However, the production of SOEC stacks has not been automated and requires manual assembly. Each cell layer is stacked between two compression discs which are tightened to hold the cells in place. With large stacks, this approach can generate variations in cell flow channel heights throughout the stack, potentially affecting cell efficiencies and thermal management of the stack. A CFD model of a single cell is developed and analyzed in ANSYS® Fluent to determine the effects of these cell variations. Cathode and Anode air flow channel heights from 1.8-2.2 mm are considered.

Mohammad Biswas, Mohammod Rahman, Mohammad Biswas (2020). Thermodynamic Process Model Development of Selected Platinum-Group Metal Catalyst Based Steam Methane Reformer for Hydrogen Production. 2020 Spring Meeting & 16th Global Congress on Process Safety. Virtual

(65a) Thermodynamic Process Model Development of Selected Platinum-Group Metal Catalyst Based Steam Methane Reformer for Hydrogen Production Reforming of hydrocarbon fuel is one of most common methods for hydrogen production and possesses a great importance in the energy industry including fuel cell system applications. Main endothermic reactions of methane reforming is steam methane reforming. Palladium-Rhodium-based and Ruthenium-based catalyst metal foams are being studied for production of hydrogen through steam methane reforming in a single-unit operation reactor. The effects of steam to methane molar feed ratio (S/M), temperature on methane conversion, H2–selectivity and thermal requirement were considered for the SMR reactor. Simulations were run using Aspen Plus. The reactor was modeled using Equilibrium and Gibbs packages to study the reactor performance. Experimental results compare the different catalysts for different S/M ratio and temperatures. H2-selectivity was insensitive to S/M ratio. As the S/M is increases the Methane conversion increases e.g. 95% conversion is achieved as the ratio is increased to 5.0. The temperature has a strong effect on methane conversion. Highest conversion is achieved above 800 C. However, the effect of pressure is not found significant which agrees with the nature of the reaction. The trends observed in this experimental SMR reactor were in good agreement with simulation model developed in this study. This work will be useful for operational optimization of such a reactor in various applications including fuel cell systems.